As the “Third Pole” of the world,the Qinghai-Tibetan
Plateau,China is located at 74°-104°E and
25°-40°N.It is known for its
high altitude,complex terrain,and harsh climate.The Qinghai-Tibetan
Plateau is one of the most sensitive regions to global climate change.It can affect the
productivity of plateau’s ecosystem.Calculating
the net primary productivity of the Qinghai-Tibetan
Plateau ecosystem is very important for accurately estimating the global carbon
cycle.As NPP cannot be directly
measured on a regional or global scale,so modelbased
estimation is the only way to proceed.In this study,we used the CEVSA model to
eatimate the NPP in the Tibetan
Plateau between 2000 and 2014, and analyzed the spatiotemporal
patterns and trends of NPP with M-K Trend test
method,the Sen’s slope
estimation method,and the Pearson correlation coefficient method.The model was
based on a 0.1°×0.1° resolution map of vegetation types,soil
texture data,and daily meteorological data.The results indicated as follows:(1)
the NPP for the Qinghai-Tibetan
Plateau decreased from southeast to northwest and was consistent with the trend
of water-heat distribution.The results were similar to
those obtained by ZHOU Caiping et al,who applied a combination of terrestrial
ecosystem model and MODIS data to estimate the net primary productivity of the
Qinghai-Tibetan
Plateau.In the spatial distribution,the NPP of the forests in the east and southeast was between 600 and 1 200 gC·m-2·a-1 and the NPP of the central grassland and meadows
was from 200 to 400 gC·m-2·a-1.In the western and northern deserts,the NPP was limited by the moisture and
temperature.(2) the annual average temperature increase had a significant
positive effect,while the precipitation decrease had a significant negative
effect on the Qinghai-Tibetan Plateau’s NPP.The
annual NPP was positively correlated
with annual mean temperature over 82.24% of the region,while negatively
correlated with annual precipitation over 49.31% of the
region.Therefore,temperature is considered to be the dominant factor
determining spatial variations in NPP.The
predecessors also obtained similar result.For example,LIU Gang et al. analyzed
the spatiotemporal variation of net primary productivity and climate controls
in China from 2001 to 2014.Based on their results,the correlation analysis
between NPP and meteorological
elements indicated that NPP was
positively correlated with temperature in the Changbai Mountain area,QinghaiTibetan
Plateau,and southern areas.(3) from 2000 to 2014,the trend of increasing NPP was consistent with the changes in
temperature.The precipitation showed a slight decrease change.A period of
warming accompanied by a decrease in precipitation contributed to the trend of
a gradual increase of NPP in Qinghai-Tibetan
Plateau.Therefore,improving our ability to accurately describe the response of NPP to climate changes will provide a
better understanding of terrestrial ecosystem responses to global
changes.However,there are still some issues to be solved,such as the uncertainty
of NPP prediction.These uncertainties
mainly include the driving variables and parameters in the model.Overall,to
predict the impact of climate change on ecosystems at the regional
level,modeling uncertainty can be reduced by increasing the spatial resolution
of the driving variables.In addition,optimizing the model parameters can also
reduce the uncertainty in the model simulation.
XU Jie, CHEN Hui-ling, SHANG Sha-sha, YANG Huan, ZHU Gao-feng, LIU Xiao-wen
.
Response of net primary productivity of Tibetan
Plateau vegetation to climate change based on CEVSA model[J]. Arid Land Geography, 2020
, 43(3)
: 592
-601
.
DOI: 10.12118/j.issn.1000-6060.2020.03.05
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